Biosensors provide an analysis of a biological fluid, such as whole blood, urine, or saliva. Typically, a biosensor analyzes a sample of the biological fluid to determine the concentration of one or more analytes, such as glucose, uric acid, lactate, cholesterol, or bilirubin, in the biological fluid. The analysis is useful in the diagnosis and treatment of physiological abnormalities. For example, a diabetic individual may use a biosensor to determine the glucose level in whole blood for adjustments to diet and/or medication.
Biosensors may be implemented using bench-top, portable, and like devices. The portable devices may be hand-held. Biosensors may be designed to analyze one or more analytes and may use different volumes of biological fluids. Some biosensors may analyze a single drop of whole blood, such as from 0.25-15 microliters (μL) in volume. Examples of portable measurement devices include the Ascensia Breeze® and Elite® meters of Bayer Corporation; the Precision® biosensors available from Abbott in Abbott Park, Ill.; Accucheck® biosensors available from Roche in Indianapolis, Ind.; and OneTouch Ultra® biosensors available from Lifescan in Milpitas, Calif. Examples of bench-top measurement devices include the BAS 100B Analyzer available from BAS Instruments in West Lafayette, Ind.; the CH Instruments' Electrochemical Workstation available from CH Instruments in Austin, Tex.; the Cypress Electrochemical Workstation available from Cypress Systems in Lawrence, Kans.; and the EG&G Electrochemical Instrument available from Princeton Research Instruments in Princeton, N.J.
Biosensors usually measure an electrical signal to determine the analyte concentration in a sample of the biological fluid. The analyte typically undergoes an oxidation/reduction or redox reaction when an input signal is applied to the sample. An enzyme or similar species may be added to the sample to enhance the redox reaction. The input signal usually is an electrical signal, such as a current or potential. The redox reaction generates an output signal in response to the input signal. The output signal usually is an electrical signal, such as a current or potential, which may be measured and correlated with the concentration of the analyte in the biological fluid.
Many biosensors have a measurement device and a sensor strip. A sample of the biological fluid is introduced into a sample chamber in the sensor strip. The sensor strip is placed in the measurement device for analysis. The measurement device usually has electrical contacts that connect with electrical conductors in the sensor strip. The electrical conductors typically connect to working, counter, and/or other electrodes that extend into a sample chamber. The measurement device applies the input signal through the electrical contacts to the electrical conductors in the sensor strip. The electrical conductors convey the input signal through the electrodes into a sample deposited in the sample chamber. The redox reaction of the analyte generates an output signal in response to the input signal. The measurement device determines the analyte concentration in response to the output signal.
The sensor strip may include reagents that react with the analyte in the sample of biological fluid. The reagents may include an ionizing agent for facilitating the redox reaction of the analyte, as well as mediators or other substances that assist in transferring electrons between the analyte and the conductor. The ionizing agent may be an oxidoreductase, such as an analyte specific enzyme, which catalyzes the oxidation of glucose in a whole blood sample. The reagents may include a binder that holds the enzyme and mediator together.
One disadvantage of the reagent compositions used in conventional biosensors is the change in measurement performance, either accuracy or precision, that occurs when the sensor strip is stored. The electronics and analysis methods used by the measurement device to determine the analyte concentration of the sample are generally selected in view of the reagent composition on the sensor strip performing as initially manufactured. However, after transportation and storage on store shelves, the reagent composition degrades with time and temperature. This change in the chemistry of the reagent composition may result in a reduction of measurement performance.
To increase the long-term stability of biosensor reagent compositions, conventional biosensors generally rely on a substantial excess of enzyme and mediator in relation to the amount of these reagents required to analyze the sample. Expecting these reagents to degrade over time, conventional reagent compositions include substantially greater amounts of enzyme and/or mediator than required to stoichiometrically react with the analyte. In addition to increasing the cost of the biosensor through the use of sacrificial reagents, the unnecessary reagents may require a larger sample volume, longer analysis time, and decrease the measurement performance of the biosensor due to many factors.
For example, PCT publication WO 88/03270 discloses an overall deposition density of 3 mg/cm2 (30 μg/mm2) with a screen printing method. The relative amount of K3Fe(CN)6 was 57.7%, phosphate buffer at 28.8%, and glucose oxidase (GO) at 3.6%. Translating these percentages into deposition densities on the sensor strip results in a K3Fe(CN)6 density of 17.31 μg/mm2, a phosphate buffer density of 8.64 μg/mm2, and a GO density of 1.08 μg/mm2. In another example, column 17, lines 25-35 of U.S. Pat. No. 4,711,245 discloses the deposition of 15 μL of a 0.1 M solution of 1,1′-dimethylferrocene in toluene onto a disk electrode having a diameter of 4 mm. With a molecular weight of 214 M.U., the 1,1′-dimethylferrocene mediator was applied at a deposition density of 25.5 μg/mm2 [(15 μL*0.1 M*214 g/mol)/22*3.14 mm2=25.5 μg/mm2]. In a further example, U.S. Pat. No. 5,958,199 discloses the deposition onto the sensor electrode of 4 μL of a solution including 40 mg of GO, 16 mg of K3Fe(CN)6, and 20 mg of CMC in 1 mL of water. In this instance, the deposition densities were 6.67 μg/mm2 for GO, 10.67 μg/mm2 for K3Fe(CN)6, and 13.33 μg/mm2 for CMC with an estimated electrode area (deposition area) of 6 mm2. In a further example, U.S. Pat. No. 5,997,817 describes a reagent formulation including 59 g of K3Fe(CN)6 dissolved in approximately 900 mL water with other ingredients. Approximately 4.5 μL of this reagent was deposited onto a 21.4 mm2 (3.2×6.7) opening to give a mediator deposition density of 13.96 μg/mm2 (4.5×10−3 mL*59 g/900 mL).
In each of these examples, the reagent compositions had mediator deposition densities in the 10-25 μg/mm2 range, while the enzyme deposition density was in the 1-6 μg/mm2 range. This large mediator loading in relation to the enzyme may be attributable to the single application of the composition to both the working and counter electrodes. Depending on sensor design, mediator may function at the counter electrode to support the electrochemical activity at the working electrode. Thus, a single reagent composition deposition covering both electrodes may result in substantially overloading the working electrode with mediator.
The examples show that excesses of enzyme and mediator are used to ensure that enough active ingredients are present for accurate glucose measurement. Using sensor strips manufactured with increased sacrificial amounts of reagents after long-term storage may result in the disadvantage of a drift in measurement performance. This drift may be observed in at least two ways: (1) a background current increase over time (affecting the calibration intercept) and (2) a shift in sensor sensitivity (affecting the calibration slope).
During storage, reduced mediator may be produced from interactions between the oxidized mediator and the enzyme system and polymer. This is a natural process believed to be governed by thermodynamics. The larger the amount of mediator or enzyme, the larger the amount of reduced mediator that is produced. As the concentration of reduced mediator increases over time, the background current will increase toward the end of the shelf-life of the sensor strips.
Multiple methods have been proposed to reduce the effect of drift on sensor performance before use of a stored sensor strip. For example, Genshaw et al. in U.S. Pat. No. 5,653,863 disclosed a method of using a relatively long initial pulse before the analysis to oxidize mediator that was reduced during transport and storage. While effective, this method lengthened the time required to complete the analysis.
Thus, it would be desirable to increase the long-term stability of the reagent composition to improve the measurement performance of the biosensor after transportation and storage. Such a long-term stability increase of the reagent composition may increase the measurement performance of the biosensor and provide a longer shelf-life for the sensor strips. It also would be desirable to reduce the amount of sacrificial enzyme and/or mediator included in the reagent composition and to decrease the time required to complete the analysis.
Another drawback of conventional biosensors used to measure the glucose concentration in whole blood (WB) samples is referred to as the “hematocrit effect.” In addition to water and glucose, WB samples contain red blood cells (RBC). Hematocrit is the volume of a WB sample occupied by RBC in relation to the total volume of the WB sample and is often expressed as a percentage. The hematocrit effect occurs when red blood cells block the diffusion of the analyte and/or mediator to one or more electrodes of the biosensor. Since the output signal measured by the biosensor corresponds to the rate of diffusion of the analyte and/or mediator, the RBC may introduce error to the analysis by interfering with this diffusion process. Thus, the greater the hematocrit percent (volume of red blood cells) deviates from the %-hematocrit system calibration for a WB sample, the greater the hematocrit bias (error) in the glucose readings obtained from the biosensor.
WB samples generally have hematocrit percentages ranging from 20 to 60%, with ˜40% being the average. If WB samples containing identical glucose levels, but having hematocrits of 20, 40, and 60%, are tested, three different glucose readings will be reported by a system based on one set of calibration constants (slope and intercept of the 40% hematocrit containing WB sample, for instance). Even though the glucose concentrations are the same, the system will report that the 20% hematocrit WB sample contains more glucose than the 40% hematocrit WB sample, and that the 60% hematocrit WB sample contains less glucose than the 40% hematocrit WB sample due to the RBC interfering with diffusion of the analyte and/or mediator to the electrode surface. Thus, conventional biosensors may not be able to distinguish between a lower analyte concentration and a higher analyte concentration where the RBC interfere with diffusion.
Conventional biosensors are generally configured to report glucose concentrations assuming a 40% hematocrit content for the WB sample, regardless of the actual hematocrit content. For these systems, any glucose measurement performed on a blood sample containing less or more than 40% hematocrit will include some hematocrit bias attributable to the hematocrit effect.
Various methods and techniques have been proposed to reduce the bias of the hematocrit effect on glucose measurements. For example, Ohara et al. in U.S. Pat. No. 6,475,372 disclosed a method of using the ratio of currents from a forward and a reverse potential pulse to compensate for the hematocrit effect. McAleer et al. in U.S. Pat. Nos. 5,708,247 and 5,951,836 disclosed a reagent formulation using silica particles to filter the RBC from the electrode surface for reducing the hematocrit effect. Carter et al. in U.S. Pat. No. 5,628,890 disclosed a method of using wide electrode spacing in combination with mesh layers to distribute the blood sample to reduce the hematocrit effect.
These conventional techniques for reducing the bias attributable to the hematocrit effect included (a) co-deposition of a polymer to minimize the hematocrit effect, (b) addition of various kinds of fused silica to enhance the filtration effect for the polymer layer, (c) compensation coefficients based on the ratio of currents from a forward and a reverse potential pulse, and (d) self-compensation by utilizing the existing solution resistance of the whole blood samples. Although these methods may be useful, conventional glucose sensors continue to exhibit significant analytical bias attributable to the hematocrit effect, generally from about 15 to 30%. Thus, it would be desirable to provide systems for quantifying analytes in biological fluids, in particular the glucose content of whole blood, which reduces bias from the hematocrit effect.